Package org.apache.spark.mllib.feature

package org.apache.spark.mllib.feature
  • Class
    Description
    ChiSqSelector
    Creates a ChiSquared feature selector.
    ChiSqSelectorModel
    Chi Squared selector model.
    ChiSqSelectorModel.SaveLoadV1_0$
     
    ElementwiseProduct
    Outputs the Hadamard product (i.e., the element-wise product) of each input vector with a provided "weight" vector.
    HashingTF
    Maps a sequence of terms to their term frequencies using the hashing trick.
    IDF
    Inverse document frequency (IDF).
    IDF.DocumentFrequencyAggregator
    Document frequency aggregator.
    IDFModel
    Represents an IDF model that can transform term frequency vectors.
    Normalizer
    Normalizes samples individually to unit L^p^ norm
    PCA
    A feature transformer that projects vectors to a low-dimensional space using PCA.
    PCAModel
    Model fitted by PCA that can project vectors to a low-dimensional space using PCA.
    PCAUtil
     
    StandardScaler
    Standardizes features by removing the mean and scaling to unit std using column summary statistics on the samples in the training set.
    StandardScalerModel
    Represents a StandardScaler model that can transform vectors.
    VectorTransformer
    Trait for transformation of a vector
    VocabWord
    Entry in vocabulary
    Word2Vec
    Word2Vec creates vector representation of words in a text corpus.
    Word2VecModel
    Word2Vec model param: wordIndex maps each word to an index, which can retrieve the corresponding vector from wordVectors param: wordVectors array of length numWords * vectorSize, vector corresponding to the word mapped with index i can be retrieved by the slice (i * vectorSize, i * vectorSize + vectorSize)